ggplot Themes and Staying DRY

Staying DRY: Don’t Repeat Yourself

• You may have noticed that as we create more and more notebooks and plots, we repeat a lot of code.
• You might also notice that a lot of styling decisions in ggplot require being repeated across multiple plots.
• In this example we will give you some techniques for making your code more DRY.

Scaffolding

• When you notice that you are repeating a lot of code, a nice and easy pattern is to create a “scaffold” file (e.g,. `scaffold.R) that contains the code you are repeating
• In this file you could include your theme.R file, but also common library imports, functions, and so on.
• All you then need to do is put something like source("scaffold.R") in your setup block.

Theme File

• I have created a scaffold.R file and a theme.R file in the examples directory
• The scaffold.R file loads libraries and sources the theme.R file
• Run it in a set up block, like below:

source(here::here("examples", "scaffold.R"))

• Now you don’t need to repeat yourself at the top of every new notebook.

Using The Theme

• This file has a theme_jhu() functions
• It extends theme_minimal() and adds a few customizations that accord with the https://brand.jhu.edu/visual-identity/colors/

Make A Plot

Below we’ll make a simple plot and quickly encounter our usual issues with styling.

p <- ggplot(mpg, aes(x = displ, y = hwy)) +
  geom_point() + 
  geom_smooth(method = "lm") +
  labs(
    title = "Fuel Efficiency by Engine Size",
    caption = "Source: mpg dataset",
    x = "Engine Size (liters)",
    y = "Fuel Efficiency (mpg)"
  )

p

Using A Theme

• In our theme.R file we have a function called theme_jhu() that looks like this
• Notice how annoying it would be to include this in every plot.

theme_jhu <- function() {
  theme_minimal(base_family = "Tahoma") +
    theme(
      plot.title = element_text(
        family = "Georgia", size = 18, hjust = 0.5, face = "bold",
        margin = margin(b = 10)
      ),
      plot.subtitle = element_text(
        hjust = 0.5, family = "Tahoma", size = 12,
        margin = margin(t = 5, b = 15)
      ),
      plot.caption = element_text(
        family = "Tahoma", size = 10, color = colors$Gray3,
        margin = margin(t = 15)
      ),
      axis.text.y = element_text(
        family = "Tahoma", size = 9, color = colors$Gray5
      ),
      axis.text.x = element_text(
        family = "Tahoma", size = 9, color = colors$Gray5
      ),
      axis.title.y = element_text(
        family = "Tahoma", size = 11,
        margin = margin(r = 15),
        face = "bold"
      ),
      axis.title.x = element_text(
        family = "Tahoma", size = 11,
        margin = margin(t = 15),
        face = "bold"
      ),
      axis.line.x = element_line(color = colors$Gray1, linewidth = 0.5),
      axis.line.y = element_line(color = colors$Gray1, linewidth = 0.5),
      panel.grid.major.x = element_line(
        color = colors$Gray1, linewidth = 0.5, linetype = "solid"
      ),
      panel.grid.minor = element_blank()
    ) +
    update_geom_defaults("smooth", list(
      color = colors$Blue,
      fill = colors$Gray2
    ))
}

Applying The Theme

• All we need to do to apply the theme is add + theme_jhu() to the end of the plot code
• This will apply the theme to the plot
• Notice how we now have JHU fonts, better spacing, etc.

p + theme_jhu()

Types of Plots

• Sometimes you want to apply a theme to a specific type of plot
• In theme.R we have a function called theme_jhu_bar() that looks like this

theme_jhu_bar <- function() {
  theme_jhu() +
    update_geom_defaults("bar", list(fill = colors$HopkinsBlue)) +
    theme(
      axis.line.x = element_blank(),
      axis.line.y = element_blank(),
      axis.ticks = element_line(color = colors$Gray1, linewidth = 0.25),
      axis.ticks.length = unit(0.2, "cm"),
      panel.border = element_blank(),
      panel.grid.major.x = element_blank(),
      panel.grid.minor = element_blank()
    )
}

Make A Bar Plot

• Let’s make a bar plot

p_bar <- ggplot(mpg, aes(x = class)) +
  geom_bar() + 
  labs(
    title = "Fuel Efficiency by Engine Size",
    caption = "Source: mpg dataset",
    x = "Class of Vehicle"
  )

p_bar

Applying The Bar Theme

All we need to do to apply the bar theme is add + theme_jhu_bar() to the end of the plot code

p_bar + theme_jhu_bar()